Data-dependent scoring parameter optimization in MS-GF+ using a spectrum quality filter
- Title
- Data-dependent scoring parameter optimization in MS-GF+ using a spectrum quality filter
- Other Titles
- spectrum quality filter를 이용한 데이터 종속적 scoring parameter 최적화
- Author
- 조현진
- Advisor(s)
- 백은옥
- Issue Date
- 2018-02
- Publisher
- 한양대학교
- Degree
- Master
- Abstract
- Most database search tools for proteomics have their own scoring parameter sets depending on experimental conditions such as fragmentation methods, instruments, digestion enzymes, and so on. These scoring parameter sets are usually predefined by tool developers and cannot be modified by users. The number of different experimental conditions grows as the technology develops, and the given set of scoring parameters could be suboptimal for tandem mass spectrometry data acquired using new sample preparation or fragmentation methods. Here we introduce a new approach to optimize scoring parameters in a data-dependent manner using a spectrum quality filter. The new approach conducts a preliminary search for the spectra selected by the spectrum quality filter. Search results from the preliminary search are used to generate data-dependent scoring parameters, then the full search over the entire input spectra are conducted using the learned scoring parameters. We show that the new approach yields more and better peptide-spectrum-matches than the conventional search using built-in scoring parameters, when compared at the same 1% false discovery rate.
- URI
- https://repository.hanyang.ac.kr/handle/20.500.11754/68618http://hanyang.dcollection.net/common/orgView/200000431965
- Appears in Collections:
- GRADUATE SCHOOL[S](대학원) > COMPUTER SCIENCE(컴퓨터·소프트웨어학과) > Theses (Master)
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